MLOps stands for “Machine Learning Operations” and is an integrative and collaborative process that helps companies to unleash the full potential of their machine learning models. Through close collaboration between data scientists and developers, MLOps enables efficient development, implementation and monitoring of models.
The automation of processes leads to faster deployments, reduced time-to-value, increased productivity and reduced risk of unproductive models. MLOps integrates seamlessly, ensuring short development cycles, quality assurance and scalability. The process steps include model creation, management, implementation and continuous monitoring. A lack of expertise in machine learning makes it difficult for companies without MLOps to use it effectively and leads to long implementation times.
MLOps is critical to optimize the use of models, minimize implementation risks and enable fast time-to-market. This approach accelerates the deployment of models and maximizes the business value of data science projects.